Instructions to use adwod/VIT_10000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adwod/VIT_10000 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="adwod/VIT_10000") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("adwod/VIT_10000") model = AutoModelForImageClassification.from_pretrained("adwod/VIT_10000", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e93b6135220538868c490fa13f78f143aae3f443363937ec11e7106e342ceb21
- Size of remote file:
- 3.52 kB
- SHA256:
- c2f0233bd18e063b01d4a5fc91e362db2f1c590901ce3032828f323f09f48aaf
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